Smart Libraries Will Power the Transition to Personalized Learning

Institutions of higher education, under increasing pressure to improve outcomes, are making well-documented and significant investments in emerging technologies.

Colleges and universities are scrambling to collect data, measure performance, and demonstrate success. At the heart of this shift lies personalized learning: technology that helps professors differentiate instruction and think differently about the delivery of instructional content.

But this trend is not limited to the classroom. Offices of Institutional Research collect and disseminate student- and program-level data. Registrar’s Offices make use of new measures of student progress. Centers for Teaching and Learning train instructors to use new tools for personalizing learning. Academic programs and departments implement all of these changes. Campus IT departments remain on the cutting edge of these initiatives, despite the transition to Software as a Service (SaaS).

Imagine the impact on access to materials, as the use of over $1 billion of buried, digital academic content is increased.

One campus unit that is not mentioned much in these discussions is the library. At first glance, it’s easy to see why. Academic libraries do not admit or graduate students. They rarely offer credit-bearing instruction. Yet libraries are one of the most powerful forces to help institutions improve instruction on campus. After all, the transition to personalized learning requires digital content; on most campuses, academic libraries have a treasure trove of digital material, licensed, catalogued, and free to students. According to the National Center for Education Statistics, in 2012, the 3,793 academic libraries in the U.S. spent over $1 billion on subscriptions to electronic resources. By the end of 2012, those libraries had 253 million e-books.

Contrast libraries’ content-abundance with a recent study that found 65% of students had not bought an assigned textbook because it was too expensive. What’s worse, the price of textbooks has increased 812% since 1978, outstripping the Consumer Price Index, healthcare costs, and even college tuition. There is a strong correlation between students’ grades and engagement with required course materials. Sadly, students knowingly risk a lower grade because they cannot afford the cost of assigned materials.

While libraries are in a unique position to help close the content-access gap, only a fraction of licensed content ever finds its way into the classroom or the dorm room. In fact, much of the library’s treasure is buried, with only 6% of the content in academic libraries ever used in conjunction with instruction. Of course, faculty can only use materials if they know it exists in the first place.

Smart libraries hold the potential to make Netflix-like content recommendations based on student outcomes or faculty preferences.

As it turns out, the key to unlocking the potential of academic libraries may come from an unexpected direction. Libraries’ digital content conundrum mirrors the problems faced by online advertisers early in the evolution of the consumer web. Massive amounts of content needed to be catalogued, indexed, filtered, and served to the right users at the right time. Today, commercial search engines index thousands of content items per second. That same approach is now being used to crawl repositories of materials owned or licensed by the library, allowing faculty to find content that relates to a specific, course-level learning objective.

Although indexing an Institution’s library repositories is substantially more challenging than open web pages, thousands of digital assets (e-books, electronic serials, audio, video) can now be crawled, indexed, enriched and matched to learning objectives each minute. Imagine the impact on access to materials, as the use of over $1 billion of buried, digital academic content is increased.

But a library’s role in powering this digital transformation doesn’t end with access. Smart libraries hold the potential to make Netflix-like content recommendations based on student outcomes or faculty preferences. Selected materials can then be pushed to the appropriate course site via the LMS. By mining their deep collection of content, tomorrow’s libraries will present the most relevant materials to instructors, enabling them to efficiently and effectively search, discover, and select the best sources to help students succeed in their courses. This isn’t science fiction; at the most advanced, competency-based institutions like Capella and Western Governors University, institutional research analysts are already using student engagement trends to develop personalized content recommendations based on a range of content qualities.

As tomorrow’s libraries gather insights on how materials are used, faculty will, in turn, receive real-time analytics about student engagement with materials and time-on-task. We can correlate students’ grades with use of the library and evaluate the content and usage patterns that lead to student performance. This is the sort of student-level data that is increasingly being used in course dashboards, to provide aggregated data about student progress. The availability of this data provides powerful levers to personalize learning for students, to support faculty in improving student outcomes, and to enable institutions of higher education to communicate their value.

David Kim is Founder and CEO of Ace Learning, a content management and analytics platform used by dozens of colleges and universities. Jeffrey Pomerantz is the author of a forthcoming book about metadata for MIT Press, and was formerly a tenured Associate Professor at the University of North Carolina at Chapel Hill.

Institutions of higher education, under increasing pressure to improve outcomes, are making well-documented and significant investments in emerging technologies.

Colleges and universities are scrambling to collect data, measure performance, and demonstrate success. At the heart of this shift lies personalized learning: technology that helps professors differentiate instruction and think differently about the delivery of instructional content.

But this trend is not limited to the classroom. Offices of Institutional Research collect and disseminate student- and program-level data. Registrar’s Offices make use of new measures of student progress. Centers for Teaching and Learning train instructors to use new tools for personalizing learning. Academic programs and departments implement all of these changes. Campus IT departments remain on the cutting edge of these initiatives, despite the transition to Software as a Service (SaaS).

Imagine the impact on access to materials, as the use of over $1 billion of buried, digital academic content is increased.

One campus unit that is not mentioned much in these discussions is the library. At first glance, it’s easy to see why. Academic libraries do not admit or graduate students. They rarely offer credit-bearing instruction. Yet libraries are one of the most powerful forces to help institutions improve instruction on campus. After all, the transition to personalized learning requires digital content; on most campuses, academic libraries have a treasure trove of digital material, licensed, catalogued, and free to students. According to the National Center for Education Statistics, in 2012, the 3,793 academic libraries in the U.S. spent over $1 billion on subscriptions to electronic resources. By the end of 2012, those libraries had 253 million e-books.

Contrast libraries’ content-abundance with a recent study that found 65% of students had not bought an assigned textbook because it was too expensive. What’s worse, the price of textbooks has increased 812% since 1978, outstripping the Consumer Price Index, healthcare costs, and even college tuition. There is a strong correlation between students’ grades and engagement with required course materials. Sadly, students knowingly risk a lower grade because they cannot afford the cost of assigned materials.

While libraries are in a unique position to help close the content-access gap, only a fraction of licensed content ever finds its way into the classroom or the dorm room. In fact, much of the library’s treasure is buried, with only 6% of the content in academic libraries ever used in conjunction with instruction. Of course, faculty can only use materials if they know it exists in the first place.

Smart libraries hold the potential to make Netflix-like content recommendations based on student outcomes or faculty preferences.

As it turns out, the key to unlocking the potential of academic libraries may come from an unexpected direction. Libraries’ digital content conundrum mirrors the problems faced by online advertisers early in the evolution of the consumer web. Massive amounts of content needed to be catalogued, indexed, filtered, and served to the right users at the right time. Today, commercial search engines index thousands of content items per second. That same approach is now being used to crawl repositories of materials owned or licensed by the library, allowing faculty to find content that relates to a specific, course-level learning objective.

Although indexing an Institution’s library repositories is substantially more challenging than open web pages, thousands of digital assets (e-books, electronic serials, audio, video) can now be crawled, indexed, enriched and matched to learning objectives each minute. Imagine the impact on access to materials, as the use of over $1 billion of buried, digital academic content is increased.

But a library’s role in powering this digital transformation doesn’t end with access. Smart libraries hold the potential to make Netflix-like content recommendations based on student outcomes or faculty preferences. Selected materials can then be pushed to the appropriate course site via the LMS. By mining their deep collection of content, tomorrow’s libraries will present the most relevant materials to instructors, enabling them to efficiently and effectively search, discover, and select the best sources to help students succeed in their courses. This isn’t science fiction; at the most advanced, competency-based institutions like Capella and Western Governors University, institutional research analysts are already using student engagement trends to develop personalized content recommendations based on a range of content qualities.

As tomorrow’s libraries gather insights on how materials are used, faculty will, in turn, receive real-time analytics about student engagement with materials and time-on-task. We can correlate students’ grades with use of the library and evaluate the content and usage patterns that lead to student performance. This is the sort of student-level data that is increasingly being used in course dashboards, to provide aggregated data about student progress. The availability of this data provides powerful levers to personalize learning for students, to support faculty in improving student outcomes, and to enable institutions of higher education to communicate their value.

David Kim is Founder and CEO of Ace Learning, a content management and analytics platform used by dozens of colleges and universities. Jeffrey Pomerantz is the author of a forthcoming book about metadata for MIT Press, and was formerly a tenured Associate Professor at the University of North Carolina at Chapel Hill.